Citation

Hua X, Yu W, Xiang Y, Zhao D, Wang W. Transp. Res. Rec. 2024; 2678(2): 76-104.

Copyright

(Copyright © 2024, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981231172965

PMID

unavailable

Abstract

The moment we face cooperative adaptive cruise control (CACC), driver takeover, that is, drivers actively take over vehicles to avoid unknown risks, is a necessary concern in reality, especially with the distrust or low acceptance of automated driving technology in the early stage of CACC development. However, the impact of driver takeover on traffic flow has not been accurately presented, as researchers only focused on the taken-over vehicle and neglected the external effects on surrounding vehicles. Departing from the literature, this study provides a novel external perspective for the impact analysis of driver takeover under a connected environment, that is, it considers the resulting communication heterogeneity and specifies multi-class conversions in the entire traffic flow. To be specific, we subdivide the dynamic process of driver takeover into 10 vehicle conversions considering vehicle degradation and platoon reorganization, then analyze their contributions to traffic stability, emissions, and fuel consumption. What is also innovative is that two forms of driver takeover are first developed in this study, which is determined by whether drivers continue opening the communication device after the takeover. On this basis, this study indicates that driver takeover has the potential to cause greater heterogeneity of the traffic flow in contrast to that in the literature and proposes theoretical models for the changed traffic flow configuration and traffic stability after the takeover. Finally, numerical experiments verify the theoretical results with discussions on multiple factors, for example, vehicle proportion, platoon length, and driving behaviors. The findings extend the external effects of driver takeover on multi-class vehicle conversions in heterogeneity traffic flow and provide a more realistic basis for the evaluation of driver takeover.

Language: en